1. Field of the Invention
This invention is related to seismic data processing. More specifically, the invention is related to a system for processing seismic data to more clearly delineate thin beds in the earth's subsurface.
2. Description of Related Art
A seismic survey is an attempt to map the subsurface of the earth by sending sound energy down into the ground and recording the reflected energy that returns from reflecting interfaces between rock layers below. On land, the source of the down-going sound energy is typically seismic vibrators or explosives. In marine environments the source is typically air guns. During a seismic survey, the energy source is moved across the earth's surface and a seismic energy signal is generated at successive locations. Each time a seismic energy signal is generated, the reflected energy is recorded at a large number of locations on the surface of the earth. In a two dimensional (2-D) seismic survey, the recording locations are generally laid out along a straight line, whereas in three-dimensional (3-D) surveys, the recording locations are distributed across the earth's surface in a grid pattern.
The seismic energy recorded at each recording location is typically referred to as a “trace”. The seismic energy recorded at a plurality of closely located recording locations will normally be combined to form a “stacked trace” and the term “traces” as used herein is intended to include stacked traces. Each trace comprises a recording of digital samples of the sound energy reflected back to the earth's surface from discontinuities in the subsurface where there is a change in acoustic impedance of the subsurface materials. The digital samples are typically acquired at time intervals between 0.001 seconds (1 millisecond) and 0.004 seconds (four milliseconds). The amount of seismic energy that is reflected from an interface depends on the acoustic impedance contrast between the rock stratum above the interface and the rock stratum below the interface. Acoustic impedance is the product of density, p, and velocity, v. The reflection coefficient, which is the ratio of amplitude of the reflected wave compared to the amplitude of the incident may be written:reflection coefficient=(ρ2v2−ρ1v1)/(ρ2v2+ρ1v1)  (Eq. 1)where,                ρ2=density of the lower layer        ρ1=density of the upper layer        v1=acoustic velocity of the lower layer, and        v2=acoustic velocity of the upper layer.        
Reflected energy that is recorded at the surface can be represented conceptually as the convolution of the seismic wavelet which is transmitted into the earth from a seismic source with a subsurface reflectivity function. This convolutional model attempts to explain the seismic signal recorded at the surface as the mathematical convolution of the downgoing source wavelet with a reflectivity function that represents the reflection coefficients at the interfaces between different rock layers in the subsurface. In terms of equations:x(t)=w(t)*e(t)+n(t)  (Eq. 2)where,                x(t) is the recorded seismogram        w(t) is the seismic source wavelet        e(t) is the earth's reflectivity function        n(t) is random ambient noise, and        * represents mathematical convolution.        
Seismic data that have been properly acquired and processed can provide a wealth of information to the explorationist. However, the resolution of seismic data is not fine enough to depict “thin” beds with clarity. Seismic resolution may be defined as the minimum separation between two seismic reflecting interfaces that can be recognized as separate interfaces on a seismic record. Where a stratum (or layer) in the earth's subsurface is not sufficiently thick, the returning reflection from the top and the bottom of the layer overlap, thereby blurring the image of the subsurface. However, even though there may be only a single composite reflection and the thickness of the layer cannot be directly observed, there is still information to be found within the recorded seismic data that may be used indirectly to estimate the actual thickness of the lithologic unit.
FIG. 1 shows a “pinch out” seismic model in which a wedge-shaped sand stratum within a shale zone gradually diminishes in thickness until it disappears at the left side of FIG. 1. FIG. 2 is a set of mathematically generated synthetic seismic traces that illustrate the convolution of a seismic wavelet with the upper and lower interfaces of this wedge shaped stratum. At the right side of FIG. 2, the seismic reflections from the upper boundary and the lower boundary of the wedge-shaped stratum are spatially separated enough so that the reflections do not overlap and the two interfaces are distinctly shown on the seismic trace. Moving to the left within FIGS. 1 and 2, the individual reflections from the upper and lower surfaces of the wedge-shaped stratum begin to merge into a single composite reflection and eventually disappear as the thickness of the wedge goes to zero. However, the composite reflection still continues to change in character after the reflections from the upper and lower surfaces merge into a single composite reflection.
It has been disclosed in Widess, How thin is a thin bed?, Geophysics, December, 1973, vol. 38, p. 1176–1180, to use calibration curves which rely on the peak-to-trough amplitude of a composite reflected thin bed event, together with the peak-to-trough time separation, to provide an estimate of the approximate thickness of the thin layer. However, a necessary step in the calibration process is to establish a “tuning” amplitude for the thin bed event in question, which occurs at the layer thickness at which maximum constructive interference occurs between the reflections from the top and base of the unit. The success of this method is limited because of the need for careful seismic processing in order to establish the correct wavelet phase and to control the relative trace-to-trace seismic trace amplitudes.
Other methods for analyzing seismic data for the presence of thin beds involve converting the data to the frequency domain and analyzing the frequency domain data. For example, a method is disclosed in U.S. Pat. No. 5,870,691 which utilizes the discrete Fourier Transform to image and map the extent of thin beds and other lateral rock discontinuities in conventional 2-D and 3-D seismic data. The method is based on the observation that the reflection from a thin bed has a characteristic expression in the frequency domain that is indicative of the thickness of the bed. A homogeneous thin bed introduces a periodic sequence of notches into the amplitude spectrum of the composite reflection, which are spaced a distance apart that is inversely proportional to the temporal thickness of the thin bed. Accordingly, the thickness of the thin beds is determined by distance by which these notches are spaced apart.
A need continues to exist, however, for an improved method for extracting thin bed information from conventionally acquired seismic data. Frequently, a thin bed is a sand bed running through shale. Knowledge of the presence of sand beds and the bed thickness is very useful information because sand is a potential hydrocarbon reservoir.
It should be noted that the description of the invention which follows should not be construed as limiting the invention to the examples and preferred embodiments shown and described. Those skilled in the art to which this invention pertains will be able to devise variations of this invention within the scope of the appended claims.